James–Stein estimator

Biased estimator for Gaussian random vectors, better than ordinary least-squared-error minimization

The James–Stein estimator is an estimator of the mean θ := ( θ 1 , θ 2 , … θ m ) {\displaystyle {\boldsymbol {\theta }}:=(\theta _{1},\theta _{2},\dots \theta _{m})} for a multivariate random variable Y := ( Y 1 , Y 2 , … Y m ) {\displaystyle {\boldsymbol {Y}}:=(Y_{1},Y_{2},\dots Y_{m})} .